{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,11]],"date-time":"2024-09-11T04:33:50Z","timestamp":1726029230606},"publisher-location":"Cham","reference-count":17,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030203504"},{"type":"electronic","value":"9783030203511"}],"license":[{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019]]},"DOI":"10.1007\/978-3-030-20351-1_64","type":"book-chapter","created":{"date-parts":[[2019,5,22]],"date-time":"2019-05-22T11:53:24Z","timestamp":1558526004000},"page":"818-829","update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Robust Biophysical Parameter Estimation with a Neural Network Enhanced Hamiltonian Markov Chain Monte Carlo Sampler"],"prefix":"10.1007","author":[{"given":"Thomas","family":"Yu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Marco","family":"Pizzolato","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Gabriel","family":"Girard","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jonathan","family":"Rafael-Patino","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Erick Jorge","family":"Canales-Rodr\u00edguez","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jean-Philippe","family":"Thiran","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2019,5,22]]},"reference":[{"key":"64_CR1","volume-title":"A Primer on Statistical Distributions","author":"N Balakrishnan","year":"2004","unstructured":"Balakrishnan, N., Nevzorov, V.B.: A Primer on Statistical Distributions. Wiley, Hoboken (2004)"},{"issue":"2","key":"64_CR2","doi-asserted-by":"publisher","first-page":"536","DOI":"10.1080\/10618600.2015.1035724","volume":"25","author":"AL Beam","year":"2016","unstructured":"Beam, A.L., Ghosh, S.K., Doyle, J.: Fast Hamiltonian Monte Carlo using GPU computing. J. Comput. Graph. Stat. 25(2), 536\u2013548 (2016)","journal-title":"J. Comput. Graph. Stat."},{"key":"64_CR3","unstructured":"Betancourt, M.: A conceptual introduction to Hamiltonian Monte Carlo. arXiv preprint \n                      arXiv:1701.02434\n                      \n                     (2017)"},{"key":"64_CR4","doi-asserted-by":"publisher","DOI":"10.1201\/b10905","volume-title":"Handbook of Markov Chain Monte Carlo","author":"S Brooks","year":"2011","unstructured":"Brooks, S., Gelman, A., Jones, G., Meng, X.L.: Handbook of Markov Chain Monte Carlo. CRC Press, Boca Raton (2011)"},{"key":"64_CR5","unstructured":"Canales Rodriguez, E.J., et al.: Unified multi-modal characterization of microstructural parameters of brain tissue using diffusion MRI and multi-echo T2 data. In: Joint Annual Meeting ISMRM-ESMRMB (2018)"},{"issue":"2","key":"64_CR6","doi-asserted-by":"publisher","first-page":"216","DOI":"10.1016\/0370-2693(87)91197-X","volume":"195","author":"S Duane","year":"1987","unstructured":"Duane, S., Kennedy, A.D., Pendleton, B.J., Roweth, D.: Hybrid Monte Carlo. Phys. Lett. B 195(2), 216\u2013222 (1987)","journal-title":"Phys. Lett. B"},{"key":"64_CR7","unstructured":"Fick, R., Wassermann, D., Deriche, R.: Mipy: an open-source framework to improve reproducibility in brain microstructure imaging. In: OHBM 2018-Human Brain Mapping, pp. 1\u20134 (2018)"},{"issue":"2","key":"64_CR8","doi-asserted-by":"publisher","first-page":"123","DOI":"10.1111\/j.1467-9868.2010.00765.x","volume":"73","author":"M Girolami","year":"2011","unstructured":"Girolami, M., Calderhead, B.: Riemann manifold Langevin and Hamiltonian Monte Carlo methods. J. Roy. Stat. Soc. Ser. B (Stat. Methodol.) 73(2), 123\u2013214 (2011)","journal-title":"J. Roy. Stat. Soc. Ser. B (Stat. Methodol.)"},{"issue":"1","key":"64_CR9","doi-asserted-by":"publisher","first-page":"97","DOI":"10.1093\/biomet\/57.1.97","volume":"57","author":"W. K. Hastings","year":"1970","unstructured":"Hastings, W.K.: Monte Carlo sampling methods using Markov chains and their applications (1970)","journal-title":"Biometrika"},{"issue":"1","key":"64_CR10","first-page":"1593","volume":"15","author":"MD Hoffman","year":"2014","unstructured":"Hoffman, M.D., Gelman, A.: The No-U-Turn sampler: adaptively setting path lengths in Hamiltonian Monte Carlo. J. Mach. Learn. Res. 15(1), 1593\u20131623 (2014)","journal-title":"J. Mach. Learn. Res."},{"key":"64_CR11","doi-asserted-by":"publisher","first-page":"346","DOI":"10.1016\/j.neuroimage.2016.06.002","volume":"139","author":"E Kaden","year":"2016","unstructured":"Kaden, E., Kelm, N.D., Carson, R.P., Does, M.D., Alexander, D.C.: Multi-compartment microscopic diffusion imaging. NeuroImage 139, 346\u2013359 (2016)","journal-title":"NeuroImage"},{"key":"64_CR12","unstructured":"Kingma, D.P., Ba, J.: Adam: a method for stochastic optimization. arXiv preprint \n                      arXiv:1412.6980\n                      \n                     (2014)"},{"issue":"1","key":"64_CR13","first-page":"430","volume":"18","author":"A Kucukelbir","year":"2017","unstructured":"Kucukelbir, A., Tran, D., Ranganath, R., Gelman, A., Blei, D.M.: Automatic differentiation variational inference. J. Mach. Learn. Res. 18(1), 430\u2013474 (2017)","journal-title":"J. Mach. Learn. Res."},{"key":"64_CR14","unstructured":"Ledoux, M.: The Concentration of Measure Phenomenon. No. 89, American Mathematical Soc. (2001)"},{"key":"64_CR15","unstructured":"Levy, D., Hoffman, M.D., Sohl-Dickstein, J.: Generalizing Hamiltonian Monte Carlo with neural networks. arXiv preprint \n                      arXiv:1711.09268\n                      \n                     (2017)"},{"issue":"1","key":"64_CR16","doi-asserted-by":"publisher","first-page":"71","DOI":"10.3233\/BPL-160033","volume":"2","author":"AL MacKay","year":"2016","unstructured":"MacKay, A.L., Laule, C.: Magnetic resonance of myelin water: an in vivo marker for myelin. Brain Plast. 2(1), 71\u201391 (2016)","journal-title":"Brain Plast."},{"issue":"4","key":"64_CR17","doi-asserted-by":"publisher","first-page":"465","DOI":"10.1080\/00401706.1995.10484391","volume":"37","author":"Sailes K. Sengijpta","year":"1995","unstructured":"Sengijpta, S.K.: Fundamentals of statistical signal processing: estimation theory (1995)","journal-title":"Technometrics"}],"container-title":["Lecture Notes in Computer Science","Information Processing in Medical Imaging"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-20351-1_64","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,5,22]],"date-time":"2019-05-22T11:59:19Z","timestamp":1558526359000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-030-20351-1_64"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"ISBN":["9783030203504","9783030203511"],"references-count":17,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-20351-1_64","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2019]]},"assertion":[{"value":"22 May 2019","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"IPMI","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Information Processing in Medical Imaging","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Hong Kong","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2019","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2 June 2019","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"7 June 2019","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"26","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ipmi2019","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/ipmi2019.cse.ust.hk\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}